Image descriptors in angiography
Hofschen K, Geissler T, Rieke N, zu Berge CS, Navab N, Demirci S (2017)
Publication Type: Conference contribution
Publication year: 2017
Journal
Publisher: Kluwer Academic Publishers
Pages Range: 283-288
Conference Proceedings Title: Informatik aktuell
Event location: Berlin, DEU
ISBN: 9783662494646
DOI: 10.1007/978-3-662-49465-3_50
Abstract
Despite recent advances in the field of image-guided interventions (IGI), the bottleneck for Angiography/X-ray guided procedures in particular is accurate and robust 2D-3D image alignment. The conventional, straight-forward parameter optimization approach is known to be ill-posed and less efficient. Retrieval-based approaches may be of superior choice here. However, this requires salient and robust image features, which can handle the difficulties of Angiographic images such as high level of noise and contrast variance. In this paper, we investigate state-of-the-art features of the field of computer vision regarding the applicability and reliability in the challenging scenario of Angiography.
Involved external institutions
Germany (DE)How to cite
APA:
Hofschen, K., Geissler, T., Rieke, N., zu Berge, C.S., Navab, N., & Demirci, S. (2017). Image descriptors in angiography. In Thomas M. Deserno, Heinz Handels, Thomas Tolxdorff, Hans-Peter Meinzer (Eds.), Informatik aktuell (pp. 283-288). Berlin, DEU: Kluwer Academic Publishers.
MLA:
Hofschen, Katharina, et al. "Image descriptors in angiography." Proceedings of the Workshops on Image processing for the medicine, 2016, Berlin, DEU Ed. Thomas M. Deserno, Heinz Handels, Thomas Tolxdorff, Hans-Peter Meinzer, Kluwer Academic Publishers, 2017. 283-288.
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